4 citations · 5 across the 9 of their papers we have counts for
8 papers · 1 filter
ReCIRC: Rectified Conformal Risk Control
Bruno Marcondes e Resende, Helton Graziadei, Thiago Rodrigo Ramos +1
Many applications of black-box predictive models require controlling task-relevant error rates, such as missed lesion pixels in segmentation or missed labels in multilabel classifi…
Learning Conditional Expectation Operators via Functional Newton Updates
Thiago Ramos, Alek Fröhlich, Daniel Perazzo +1
We introduce the Functional Spectral-Newton Method (FSNM) for learning the leading singular structure of a conditional expectation operator without fixing a basis or reproducing ke…
Conformal Prediction via Transported Beta Laws
Thiago R. Ramos, Helton Graziadei, Luben M. C. Cabezas
Split conformal prediction provides finite-sample marginal coverage under exchangeability, but this guarantee averages over the random calibration sample. We study instead the law…
LOCUS: A Distribution-Free Loss-Quantile Score for Risk-Aware Predictions
Matheus Barreto, Mário de Castro, Thiago R. Ramos +2
Modern machine learning models can be accurate on average yet still make mistakes that dominate deployment cost. We introduce Locus, a distribution-free wrapper that produces a per…
LoBoost: Fast Model-Native Local Conformal Prediction for Gradient-Boosted Trees
Vagner Santos, Victor Coscrato, Luben Cabezas +2
Gradient-boosted decision trees are among the strongest off-the-shelf predictors for tabular regression, but point predictions alone do not quantify uncertainty. Conformal predicti…
Conformal Prediction for Compositional Data
Lucas P. Amaral, Luben M. C. Cabezas, Thiago R. Ramos +1
Dirichlet regression models are suitable for compositional data, in which the response variable represents proportions that sum to one. However, there are still no well-established…
CP4SBI: Local Conformal Calibration of Credible Sets in Simulation-Based Inference
Luben M. C. Cabezas, Vagner S. Santos, Thiago R. Ramos +2
Current experimental scientists have been increasingly relying on simulation-based inference (SBI) to invert complex non-linear models with intractable likelihoods. However, poster…
Epistemic Uncertainty in Conformal Scores: A Unified Approach
Luben M. C. Cabezas, Vagner S. Santos, Thiago R. Ramos +1
Conformal prediction methods create prediction bands with distribution-free guarantees but do not explicitly capture epistemic uncertainty, which can lead to overconfident predicti…